1. Field of the Invention
The present invention provides a method of data transformation, and more particularly, to a method of encoding and decoding image data by applying an image capturing device.
2. Description of the Prior Art
A rear part of a chip of a digital camera usually includes a large buffer to store necessary image data during calculation to complete necessary calculations of two-dimensional image data. However, in ordinary chips, the square measure of the buffer is always too large so that the cost of production is increased significantly. Under the presupposition that the images can be recognized by the naked eye, the size of the buffer is capable of being decreased by encoding techniques. Therefore the square measure of the chip is capable of being decreased significantly so that it is more convenient to use the chip, and that the production is decreased.
Prior art techniques for implementing image encoding include adaptive difference pulse coding and difference pulse coding methods. The principle of such techniques is reducing the amount of the image data to be decoded by taking advantage of the significant associability between adjoining pixels. Such techniques are not too difficult to be implemented. However, under some particular circumstances, for example, on the fringe of the image, where the variation of adjoining pixels is much more pronounced, the associability between adjoining pixels is decreased significantly. Therefore, the quality of image decoding in such implementations is decreased significantly.
Prior art techniques also frequently take advantage of the discrete cosine transform (DCT) so that the pixels (also called the parameters) are transformed from the time domain to the frequency domain and classified as low-frequency pixels and high-frequency pixels. A two-dimensional transform is sometimes used for performing the DCT, wherein the number of the sampled pixels during a single execution is 64 (an 8-by-8 array). Among the 64 pixels, all the pixels are high-frequency pixels except for the first pixel, which is a low-frequency pixel. Taking into account that low-frequency pixels are more likely to be important elements of the image, low frequency pixels are encoded with low distortion while high-frequency pixels are encoded with higher distortion (and consequently more compact encoding). Lastly, the inverse discrete cosine transform (IDCT) is performed so that the pixels are transformed from the frequency domain to the time domain. However, many bits used in performing the DCT causes a bottleneck in efficiency and storage. Therefore methods requiring fewer bits and less transforms between the time domain and the frequency domain are necessary.